Use when the user wants to verify cold emails, enrich a lead list, or autonomously guess email addresses from a CSV using ValidEmail.co or the open-source Reacher engine.
npx skills add https://github.com/Varnan-Tech/opendirectory --skill cold-email-verifier
This skill autonomously processes a CSV of leads (containing First Name, Last Name, and Company Name), discovers their corporate domain, generates professional email permutations, and strictly verifies their deliverability.
It is designed to solve the problem of missing contact info by guessing core email angles and then checking which one is real.
You don't need to provide emails in your CSV! If the CSV only contains First Name, Last Name, and Company Name, the script will automatically:
Once the emails are guessed, the script must verify them. We support three methods:
The absolute best option. ValidEmail.co provides enterprise-grade accuracy, bypasses strict catch-all servers, and handles IP reputation for you.
If you want a 100% free, open-source solution, you can host the Reacher backend yourself on a cloud provider (like AWS, GCP, or Hetzner).
You can run the Reacher CLI directly on your laptop.
First, ensure dependencies are installed: pip install -r requirements.txt
To use ValidEmail.co (Recommended):
`ash
export VALIDEMAIL_API_KEY="your_api_key_here"
python scripts/email_verifier.py --input leads.csv --output verified_leads.csv --mode validemail
`
To use Self-Hosted Reacher:
`ash
python scripts/email_verifier.py --input leads.csv --output verified_leads.csv --mode reacher-http --reacher-url "http://your-server-ip:8080/v0/check_email"
`
The input CSV must contain these exact column headers (or their specific mappings):
Analyzes meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.
Toolkit for creating animated GIFs optimized for Slack, with validators for size constraints and composable animation primitives. This skill applies when users request animated GIFs or emoji animations for Slack from descriptions like "make me a GIF for Slack of X doing Y".
Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack.
A skill that creates new Claude skills and automatically shares them on Slack using Rube for seamless team collaboration and skill discovery.
Automate Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify, etc.) using agent-browser via Chrome DevTools Protocol. Use when the user needs to interact with an Electron app, automate a desktop app, connect to a running app, control a native app, or test an Electron application. Triggers include "automate Slack app", "control VS Code", "interact with Discord app", "test this Electron app", "connect to desktop app", or any task requiring automation of a native Electron application.
Prepare meeting materials with Notion context and Codex research; use when gathering context, drafting agendas/pre-reads, and tailoring materials to attendees.
Interactive daily standup/meeting update generator. Use when user says 'daily', 'standup', 'scrum update', 'status update', 'what did I do yesterday', 'prepare for meeting', 'morning update', or 'team sync'. Pulls activity from GitHub, Jira, and Claude Code session history. Conducts 4-question interview (yesterday, today, blockers, discussion topics) and generates formatted Markdown update.
Take varnan-tech/cold-email-verifier from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip.
Without those the skill loads but fails at the first command.